An integrated spatial planning model for climate change adaptation in coastal zones

Ko, Tsung-Ting; Chang, Yang‐Ming

doi:10.1016/j.ocecoaman.2012.05.021

Cited by 18 publications

(11 citation statements)

References 19 publications

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“…Huang et al (1998) [17] proposed an inexact-fuzzy multi-objective programming model for adaptation planning of land resources management in the Mackenzie Basin under changing climate. Ko [18] and Chang (2012) developed an integrated modeling framework called MOPSD (Multi-Objective Programming and System Dynamic) that can be used for spatial land use planning in coastal areas. Gong et al (2012) [19] constructed a multi-objective model to discuss the problem, including economic benefits and ecological effectiveness, in terms of land use optimization.…”

Section: Multi-objective Land Use Planning Researchmentioning

confidence: 99%

A Multi-Objective Spatial Optimization Method for Land Use Allocation in High Flood Risk Areas

Huang¹,

Kuo

Tsou³

2013

IJBBB

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As the result of the rapid development, mountain areas have suffered from the unbalanced development and land use planning. Recently, under the global climate change, the stability of mountain land is more difficult to control. Therefore, it is an important issue to find the most suitable land use pattern for mountains in order to respond to the impact of global climate change.This paper applies multi-objective programming model for the evaluation of sustainable management strategies of optimal land development in mountains. The environmental goals focus on the water quality, the economic goals focus on the total output value, and the disaster goals focus on soil erosion. A case study of the planning for land use programs in the Tai Po Township in Taiwan was demonstrated

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Section: Multi-objective Land Use Planning Researchmentioning

confidence: 99%

A Multi-Objective Spatial Optimization Method for Land Use Allocation in High Flood Risk Areas

Huang¹,

Kuo

Tsou³

2013

IJBBB

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“…This has resulted in significant land subsidence: Across the southwest of Taiwan, an area of nearly 900 km 2 is afflicted by an annual average subsidence rate exceeding 3 cm [15]. These alarming rates, alongside high levels of development and population density, and increasing the frequency of intense weather-related flood events and resulting in the coast of south west being deemed one of the most vulnerable regions in Taiwan [16][17][18][19]. This region is therefore the central focus for this paper.…”

Section: Introductionmentioning

confidence: 99%

Development and application of a Socioeconomic Vulnerability Indicator Framework (SVIF) for Local Climate Change Adaptation in Taiwan

et al. 2020

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This paper outlines the development of a socioeconomic vulnerability indicator framework (SVIF) which was designed to provide a tool to inform bespoke local adaptation actions along the Taiwanese coast. The framework incorporates a range of diverse indicators, from ones that are related to demographic characteristics to others that represent economic and infrastructure features. As such, the framework encapsulates multiple and complex dimensions of socio-economic vulnerability rather than deriving a less nuanced single index; this is an approach that, whilst more commonly employed elsewhere, may mask critical features of socioeconomic vulnerability at local levels. The paper describes the piloting of the SVIF as it quantifies and visually summarizes the susceptibility and resilience of four townships (Mailiao, Kauho, Linbian and Jiadong) along the exposed coast of Southwest Taiwan. The paper demonstrates the SVIF's potential in characterizing specific aspects of socio-economic vulnerability that local decision-makers could use to tailor local adaptation. The SVIF was successful in differentiating between the four local areas, highlighting clear differences between urban and rural townships. With further development by using a more participative approach and expanding its application to wider geographical contexts both in Taiwan and further afield, the authors are confident that the SVIF has the potential to provide a useful tool for local adaptation.

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“…As a result most GIS-based applications of multi objective optimization use raster-based data as their input (Cao et al, 2011;Karakostas & Economou, 2013;Klein, Holzkamper, Calanca, Seppelt, & Fuhrer, 2013;Ko & Chang, 2012;Porta et al, 2013). Using a rasterbased representation of a planning region Janssen, van Herwijnen, Stewart, and Aerts (2008) showed that it was possible to formulate a spatial planning problem in mathematical terms and apply multi objective optimization to generate optimal solutions interactively.…”

Section: Introductionmentioning

confidence: 99%

A spatial optimization algorithm for geodesign

Eikelboom

Janssen

Stewart

2015

Landscape and Urban Planning

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An integrated spatial planning model for climate change adaptation in coastal zones

Cited by 18 publications

References 19 publications

A Multi-Objective Spatial Optimization Method for Land Use Allocation in High Flood Risk Areas

A Multi-Objective Spatial Optimization Method for Land Use Allocation in High Flood Risk Areas

Development and application of a Socioeconomic Vulnerability Indicator Framework (SVIF) for Local Climate Change Adaptation in Taiwan

A spatial optimization algorithm for geodesign

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